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Time Series Analysis of the Dynamics of Merger and Acquisition Cycles in the Global Water Sector

Author

Listed:
  • Manuel Monge

    (Faculty of Law, Business and Government, Universidad Francisco de Vitoria, E-28223 Madrid, Spain)

  • Rafael Hurtado

    (Faculty of Business, Economics and Law, CUNEF Universidad, E-28040 Madrid, Spain)

  • Juan Infante

    (Faculty of Social Science and Law, Universidad Villanueva, E-28034 Madrid, Spain)

Abstract

This paper examined the cyclical patterns of mergers and acquisitions (M&A) in the global water sector from 1982 to 2024, with a focus on both linear and nonlinear dynamics in M&A waves. Through a univariate analysis using ARFIMA models, we found that the data exhibited stationary behavior, meaning that in response to an exogenous shock, the series is likely to revert to its original trend over time. Additionally, the non-parametric Brock, Dechert, and Scheinkman (BDS) test revealed the complex and irregular nature of M&A cycles within the sector. To account for this complexity, we applied the Markov-switching dynamic regression (MS-DR) model, which shows that once the industry enters a high-activity regime, it tends to persist in this state for extended periods. This suggests that external shocks or trends—such as regulatory reforms or global water scarcity concerns—are key drivers that trigger and sustain waves of M&A activity in the sector.

Suggested Citation

  • Manuel Monge & Rafael Hurtado & Juan Infante, 2025. "Time Series Analysis of the Dynamics of Merger and Acquisition Cycles in the Global Water Sector," Mathematics, MDPI, vol. 13(7), pages 1-13, March.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:7:p:1146-:d:1624673
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